'what calls' 검색 결과

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

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Symbol-level navigation of a local checkout using tree-sitter ASTs. Answers where a symbol is defined, what lines it spans, which symbols a file exposes, what a directory holds, and where a name is referenced — every answer carries exact line ranges to feed straight into a scoped read. Use for "where is X defined", "who calls X", "find the function/class named", "what's in this file", "give me the line range for", "show me the source of", "list the symbols in", or before editing a file you have not read. Each invocation auto-scans and is self-contained. Not for first-encounter repo orientation (use exploring-codebases), for what a codebase DOES rather than what it contains (featuring), for binding-resolved Python caller sets (searching-codebases), or for literal text and regex matching (plain ripgrep).

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Flip a problem, goal, or decision 180 degrees to find what forward thinking misses. Asks what would guarantee failure, then works backward to what must be avoided or changed. Load when the user says "invert this", "flip this problem", "what would guarantee failure", "think backward", "reverse engineer the goal", "think about it backwards", or when deep-thinking diagnoses an inversion frame. Also triggers on "what's the opposite of success here", "how would we sabotage this". Two methods: Failure Inversion and Opposite Goal. Max 2 clarifying questions before inverting. Always returns forward actions. For broader analysis, deep-thinking calls this.

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Use the Dial CLI to send and receive SMS, place AI voice calls, and manage real phone numbers. It explains workflows for waiting for verification codes, checking completed calls, and processing command results.

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• Send an SMS to a specified number
• Place a call handled by an AI voice agent
• Wait for an SMS verification code

Prepare for the next seven days of customer and prospect calls with one chronological briefing. Gather company and attendee research, highlight urgent account signals and notable news, and suggest meeting objectives using Common Room as the primary source.

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• Preparing for a week of customer calls
• Reviewing companies and attendees before meetings
• Spotting renewal risks and expansion opportunities

Find customers’ exact words about a feature, objection, or competitor across meeting transcripts and emails. Organize quotes with speaker details, dates, sources, and context, while showing which accounts lack source coverage.

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• Collect customer quotes about a feature
• Review objections raised during sales calls
• Find customer comments about competitors

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

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Use when a question is about *structure* rather than text - who calls or launches a symbol, where it is defined, what a change would reach, whether something is dead, how a request gets from the API to a kernel. Triggers on "who calls", "who launches this kernel", "where is X defined", "what breaks if I change", "is this still used", "is this dead", "trace the path from X to Y", "blast radius", "what depends on this header". Do NOT use for free-text search (`rg` is better and cheaper) or to open a file whose path you already know.

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Explore the context-matic MCP server through an interactive tour. Discover available APIs, choose one, and review authentication, data structures, and example calls in your project's programming language, with guidance matched to the SDK version.

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• Learning what the context-matic server can do
• Browsing APIs available for a project's language
• Exploring an API's authentication and quickstart

Explore code structure and history using an index of code relationships and meaning-based search. Trace calls, assess change impact, find likely bug locations, generate architecture reports, and review pull requests for risk and conflicts.

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• Tracing function calls and change impact
• Investigating code locations related to a GitHub issue
• Generating architecture reports and class diagrams

Query the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).

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Protocol for handling ambiguous decisions and missing/conflicting knowledge during code generation, design, and review. Ensures AI surfaces genuine judgment calls with structured options and stops on hallucination risk instead of silently assuming. Use when a decision has multiple valid approaches, when facts are missing or contradictory, when the user asks 'what should we do here?', 'is this a judgment call?', 'should I ask about this?', 'am I guessing here?', 'what are the tradeoffs?', or when deciding between two reasonable architectural or design options. Also composed by molecules to define how judgment calls and clarification requests are surfaced and resolved.

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OpenClaw API gateway proxy for authenticated SaaS calls (100+ services in references/SERVICES.md). Use ONLY when making an HTTP request to a third-party service that requires the gateway's stored credentials. NOT for direct API calls with bearer tokens already in scope, NOT for monday.com (use monday-for-agents), NOT for WhatsApp (use heleni-whatsapp). Triggers: "call the X API", "fetch from <service>", "send to Slack via gateway", "use the gateway for".

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Map symbol dependencies, callers, and blast radius before editing code. Load when the user asks what depends on a symbol, what breaks if they change something, blast radius of a change, reverse dependencies, or which tests cover a function. Also triggers on "who calls this", "impact of changing", "dependency map", "what uses this", "find callers", or before any non-trivial edit when safe-change is not yet active. Pairs with codebase-understanding for broad architecture; this skill is symbol-scoped and edit-gated.

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개발 요청에 필요한 변경 범위를 확인하고 기존 코드와 표준 기능으로 문제 전체를 해결하는 최소 구현을 안내합니다. 관련 부분의 수정, 필요한 테스트와 짧은 보고도 중시합니다.

• 요청을 충족하는 최소 구성 구현
• 호출부를 확인해 공통 코드의 결함 수정
• 불필요한 의존성과 추상화 방지

Set up rules that allow or block Claude Code tool calls, and record executed tool names in digitally signed receipts. The skill also explains offline verification and the limits of what those records prove.

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• Restricting which Claude Code tools may run
• Recording tool names in digitally signed receipts
• Verifying receipts offline with a public key

Identify runtime signs of attackers breaking out of Docker or Kubernetes containers. Review namespace changes, privilege abuse, sensitive host access, and unusual system calls to guide incident investigations and compare monitoring coverage across security tools.

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• Investigating a suspected Docker or Kubernetes container escape
• Choosing runtime behaviors to monitor for escape attempts
• Comparing escape detection coverage across security sensors

Turn voice calls into GBrain records containing transcripts, summaries, audio links, and references to people or companies. The workflow also sends summaries to a configured messaging service; automatic processing when calls end requires additional implementation.

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• Keep a transcript and summary of a voice call
• Review call decisions alongside the original audio
• Link call records to people and company pages

Draft marketing content for blogs, social media, newsletters, landing pages, press releases, and case studies. Use channel-specific structures to shape headlines, search-friendly copy, and calls to action that tell readers what to do next.

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• Draft a blog post with keywords and a meta description
• Write social posts suited to each platform
• Create newsletter subject lines and body copy

Explore relationships between functions and files using a prebuilt code graph, a map of code dependencies. Trace bugs, inspect callers and execution paths, and assess the impact of refactoring or proposed changes.

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• Explore callers and dependencies in unfamiliar code
• Trace a bug across multiple files
• Assess the impact of renaming or removing code

Find where code lives, understand how it works, and trace connections between functions using a repository index. Results include file locations and line numbers to help plan edits and assess which other code a change could affect.

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• Understanding an unfamiliar codebase
• Finding where a behavior is implemented
• Checking the impact of renaming a function

Find where code lives, understand how it works, and trace connections between functions using a repository index. Results include file locations and line numbers to help plan edits and assess which other code a change could affect.

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• Understanding an unfamiliar codebase
• Finding where a behavior is implemented
• Checking the impact of renaming a function

Keep a dated communication log for each legal clinic case, covering calls, emails, meetings, and other contacts. Summarize conversations and action items, review recent history, and flag unanswered messages or missed follow-ups for supervision and handoffs.

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• Recording a client call or email
• Checking what the client was told previously
• Finding unanswered messages and missed follow-ups

Add file-based observability, tracing, and run analysis to LLM/agent experiments — per-turn transcripts, tool calls and results, reasoning traces, token/cost accounting, per-episode artifacts, plus terminal viewers and a run-comparison report. Platform-agnostic: one small adapter covers OpenAI, Gemini/Vertex, Anthropic, LiteLLM, Tinker, vLLM, or any custom inference stack, and the same tooling then works unchanged. Use this skill whenever the user wants observability, tracing, logging, or run tracking for model experiments; asks why an agent failed a task or wants to replay/debug/diff an episode; wants to compare models, arms, or ablations; wants to instrument a new folder, repo, or platform ("add observability here", "do the same for Tinker/Gemini/OpenAI"); wants to import or tie in existing experiment results so old runs show up alongside new ones; or wants eval runner scripts where many models share one protocol. Reach for this even when they only say "log what the model is doing", "I can't tell what happened in this run", or "set up traces for this experiment".

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